Summary: For example, DenseElementsAttr currently does not properly round-trip unsigned integer values.
Differential Revision: https://reviews.llvm.org/D75374
Summary:
NFC - Moved StandardOps/Ops.h to a StandardOps/IR dir to better match surrounding
directories. This is to match other dialects, and prepare for moving StandardOps
related transforms in out for Transforms and into StandardOps/Transforms.
Differential Revision: https://reviews.llvm.org/D74940
Thus far IntegerType has been signless: a value of IntegerType does
not have a sign intrinsically and it's up to the specific operation
to decide how to interpret those bits. For example, std.addi does
two's complement arithmetic, and std.divis/std.diviu treats the first
bit as a sign.
This design choice was made some time ago when we did't have lots
of dialects and dialects were more rigid. Today we have much more
extensible infrastructure and different dialect may want different
modelling over integer signedness. So while we can say we want
signless integers in the standard dialect, we cannot dictate for
others. Requiring each dialect to model the signedness semantics
with another set of custom types is duplicating the functionality
everywhere, considering the fundamental role integer types play.
This CL extends the IntegerType with a signedness semantics bit.
This gives each dialect an option to opt in signedness semantics
if that's what they want and helps code sharing. The parser is
modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as
signed and unsigned integer types, respectively, leaving the
original `i[1-9][0-9]*` to continue to mean no indication over
signedness semantics. All existing dialects are not affected (yet)
as this is a feature to opt in.
More discussions can be found at:
https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ
Differential Revision: https://reviews.llvm.org/D72533
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
* Fixes use of anonymous namespace for static methods.
* Uses explicit qualifiers(mlir::) instead of wrapping the definition with the namespace.
PiperOrigin-RevId: 286222654
tensorflow/mlir#162 introduced a bug that
incorrectly allowed fusion of producer loops with multiple outgoing
edges. This commit fixes that problem. It also introduces a new flag to
disable sibling loop fusion so that we can test producer-consumer fusion
in isolation.
Closestensorflow/mlir#259
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/259 from dcaballe:dcaballe/fix_multi_out_edge_producer_fusion 578d5661705fd5c56c555832d5e0528df88c5282
PiperOrigin-RevId: 283531105
This CL utilizies the more robust fusion feasibility analysis being built out in LoopFusionUtils, which will eventually be used to replace the current affine loop fusion pass.
PiperOrigin-RevId: 281112340
This PR is a stepping stone towards supporting generic multi-store
source loop nests in affine loop fusion. It extends the algorithm to
support fusion of multi-store loop nests that:
1. have only one store that writes to a function-local live out, and
2. the remaining stores are involved in loop nest self dependences
or no dependences within the function.
Closestensorflow/mlir#162
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/162 from dcaballe:dcaballe/multi-output-fusion 7fb7dec6fe8b45f5ce176f018bfe37b256420c45
PiperOrigin-RevId: 273773907
- allow symbols in index remapping provided for memref replacement
- fix memref normalize crash on cases with layout maps with symbols
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Reported by: Alex Zinenko
Closestensorflow/mlir#139
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/139 from bondhugula:memref-rep-symbols 2f48c1fdb5d4c58915bbddbd9f07b18541819233
PiperOrigin-RevId: 269851182
Refactor replaceAllMemRefUsesWith to split it into two methods: the new
method does the replacement on a single op, and is used by the existing
one.
- make the methods return LogicalResult instead of bool
- Earlier, when replacement failed (due to non-deferencing uses of the
memref), the set of ops that had already been processed would have
been replaced leaving the IR in an inconsistent state. Now, a
pass is made over all ops to first check for non-deferencing
uses, and then replacement is performed. No test cases were affected
because all clients of this method were first checking for
non-deferencing uses before calling this method (for other reasons).
This isn't true for a use case in another upcoming PR (scalar
replacement); clients can now bail out with consistent IR on failure
of replaceAllMemRefUsesWith. Add test case.
- multiple deferencing uses of the same memref in a single op is
possible (we have no such use cases/scenarios), and this has always
remained unsupported. Add an assertion for this.
- minor fix to another test pipeline-data-transfer case.
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#87
PiperOrigin-RevId: 265808183
Switch to C++14 standard method as llvm::make_unique has been removed (
https://reviews.llvm.org/D66259). Also mark some targets as c++14 to ease next
integrates.
PiperOrigin-RevId: 263953918
Since raw pointers are always passed around for IR construct without
implying any ownership transfer, it can be error prone to have implicit
ownership transferred the same way.
For example this code can seem harmless:
Pass *pass = ....
pm.addPass(pass);
pm.addPass(pass);
pm.run(module);
PiperOrigin-RevId: 263053082
These methods assume that a function is a valid builtin top-level operation, and removing these methods allows for decoupling FuncOp and IR/. Utility "getParentOfType" methods have been added to Operation/OpState to allow for querying the first parent operation of a given type.
PiperOrigin-RevId: 257018913
In most places, this is just a name change (with the exception of affine.dma_start swapping the operand positions of its tag memref and num_elements operands).
Significant code changes occur here:
*) Vectorization: LoopAnalysis.cpp, Vectorize.cpp
*) Affine Transforms: Transforms/Utils/Utils.cpp
PiperOrigin-RevId: 256395088
Move the data members out of Function and into a new impl storage class 'FunctionStorage'. This allows for Function to become value typed, which will greatly simplify the transition of Function to FuncOp(given that FuncOp is also value typed).
PiperOrigin-RevId: 255983022
*) Factors slice union computation out of LoopFusion into Analysis/Utils (where other iteration slice utilities exist).
*) Generalizes slice union computation to take the union of slices computed on all loads/stores pairs between source and destination loop nests.
*) Fixes a bug in FlatAffineConstraints::addSliceBounds where redundant constraints were added.
*) Takes care of a TODO to expose FlatAffineConstraints::mergeAndAlignIds as a public method.
--
PiperOrigin-RevId: 250561529
*) Adds LoopFusionUtils which will expose a set of loop fusion utilities (e.g. dependence checks, fusion cost/storage reduction, loop fusion transformation) for use by loop fusion algorithms. Support for checking block-level fusion-preventing dependences is added in this CL (additional loop fusion utilities will be added in subsequent CLs).
*) Adds TestLoopFusion test pass for testing LoopFusionUtils at a fine granularity.
*) Adds unit test for testing dependence check for block-level fusion-preventing dependences.
--
PiperOrigin-RevId: 249861071
Trying to activate both LLVM and MLIR passes in mlir-cpu-runner showed name collisions when registering pass names.
One possible way of disambiguating that should also work across dialects is to prepend the dialect name to the passes that specifically operate on that dialect.
With this CL, mlir-cpu-runner tests still run when both LLVM and MLIR passes are registered
--
PiperOrigin-RevId: 246539917
* dyn_cast_or_null
- This will first check if the operation is null before trying to 'dyn_cast':
Value *v = ...;
if (auto forOp = dyn_cast_or_null<AffineForOp>(v->getDefiningOp()))
...
* isa_nonnull
- This will first check if the pointer is null before trying to 'isa':
Value *v = ...;
if (isa_nonnull<AffineForOp>(v->getDefiningOp());
...
--
PiperOrigin-RevId: 242171343
River Riddle